1. Field of the Invention
The present invention relates to image processing for outputting a video signal (image data) obtained by processing an input video signal (input image data) and, more particularly, to image processing for transforming the gradation characteristic of a video signal on the basis of the transitional direction of the brightness of a video scene.
2. Description of the Related Art
A video display apparatus such as a television executes signal processing of executing gradation transform of a video signal. In this signal processing, predetermined gradation transform of a video signal is executed in consideration of the characteristic of the display and the contrast and gradation level of video data itself. For example, a process called black stretch allocates a lot of black gradation steps to a video signal, thereby improving black expression. A liquid crystal TV executes inverse transform (inverse gamma conversion) to cancel gradation transform which a broadcaster has executed for a video signal and make the video signal have a linear gradation characteristic and then displays a video image.
In general, gradation transform is often executed by using a lookup table (LUT). The data of an LUT contains the sets of inputs and outputs corresponding to them. Upon receiving data, the LUT outputs data corresponding to the input data. An LUT used in, for example, a video display apparatus often has an input-output characteristic that draws a curve. This curve is generally called a gamma conversion curve or a gamma curve.
A technique called a dynamic gamma process has recently been invented, which executes optimum gradation transform for each scene (single frame or a plurality of frames) of video data. In this process, input data is corrected to visually optimize the image of each scene in accordance with the pixel value distribution of each scene or the degree of change between scenes.
However, the dynamic gamma process executes gradation transform without considering the adaptability of eyes. For this reason, the video contrast sometimes visually lowers when the scene changes. For example, when bright scenes continue, the eyes adapt to the bright image region, and their sensitivity to a dark image region becomes low. If a dark scene follows consecutive bright scenes, the user cannot see the dark scene well.